Link Analysis for Communities Detection on Facebook
Abstract
Social networks have become a part in the daily life of millions of users, which offer wide range of interests and practices. The main characteristic of social networks is its ability to gather different individuals around a common point of view or collective beliefs. Among the current social networking sites, Facebook is the most popular, which has the highest number of users. However, in Facebook, the existence of communities (groups)is a critical question; thus, many researchers focus on potential communities by using techniques like data mining and web mining. In this work, we present four approaches based on link analysis techniques to detect prospective groups and their members
Cite
@article{arxiv.1406.6705,
title = {Link Analysis for Communities Detection on Facebook},
author = {Mohamed Adnane Mellah and Abdelmalek Amine and Reda Mohamed Hamou and A. V. Senthil Kumar},
journal= {arXiv preprint arXiv:1406.6705},
year = {2014}
}
Comments
15 pages, 7 figures, International Journal of Data Mining And Emerging Technologies, 2014, Volume 4, Issue 1